Teaching

The following courses are taught by Pascal Fua and members of the CVLab.

CS-442 Computer Vision

The course introduces the basic techniques of the field of Computer Vision. The students will learn to apply Deep Machine Learning, Geometry, and Image Processing techniques where appropriate.

The course is taught by Prof. Pascal Fua in spring semesters.
Coursebook: Computer-Vision-CS-442

CS-233 Introduction to Machine Learning

The course introduces basic Machine Learning techniques, with a focus on Computer Vision applications.

The course is taught by Prof. Pascal Fua in spring semesters.
Coursebook: Introduction to Machine Learning-CS-233

CS-211 Introduction to Visual Computing

This course is the entry point of the theme ‘visual computing’ that continues in the curriculum in computer science at the bachelor and master. It explores the role of images, static or animated, in the interaction between a computer, users and their environment.

The course is taught by Mathieu Salzmann and Prof. Pierre Dillenbourg in spring semesters.
Coursebook: Introduction-to-Visual-Computing-CS-211

DH-406 Signal Processing and Machine Learning for the Digital Humanities

This course aims to introduce the basic principles of signal processing and machine learning in the context of the digital humanities. Exercises, numerical examples and computer sessions will allow the students to acquire a practical understanding of the techniques studied in class.

The cause is taught by Mathieu Salzmann and Prof. Andrea Ridolfi in fall semesters.
Coursebook: Signal-Processing-and-Machine-Learning-for-the-Digital-Humanities-DH-406